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This review paper uses renormalization group techniques for signal detection in nearly-continuous positive spectra. We highlight universal aspects of the analogue field-theory approach. The first aim is to present an extended…

High Energy Physics - Theory · Physics 2025-11-27 Vincent Lahoche , Dine Ousmane Samary , Mohamed Tamaazousti

The Renormalization Group (RG) is a set of methods that have been instrumental in tackling problems involving an infinite number of degrees of freedom. What all these methods have in common -- which is what explains their success -- is that…

Statistical Mechanics · Physics 2020-04-30 Pedro Pessoa , Ariel Caticha

We present a simple and consistent way to compute correlation functions in interacting theories with non-trivial phase diagram. As an example we show how to consistently compute the four-point function in three dimensional…

High Energy Physics - Theory · Physics 2016-07-13 Alessandro Codello , Alberto Tonero

An exact renormalization group equation is derived for the free energy of matrix models. The renormalization group equation turns out to be nonlinear for matrix models, as opposed to linear for vector models. An algorithm for determining…

High Energy Physics - Theory · Physics 2009-10-22 Saburo Higuchi , Chigak Itoi , Shinsuke Nishigaki , Norisuke Sakai

A model Hamiltonian that exhibits asymptotic freedom and a bound state, is used to show on example that similarity renormalization group procedure can be tuned to improve convergence of perturbative derivation of effective Hamiltonians,…

High Energy Physics - Theory · Physics 2009-11-07 Stanislaw D. Glazek , Jaroslaw Mlynik

This work unifies pseudo-time and inexact regularization techniques for nonmonotone classes of partial differential equations, into a regularized pseudo-time framework. Convergence of the residual at the predicted rate is investigated…

Numerical Analysis · Mathematics 2016-11-29 Sara Pollock

Soliton solutions are recovered as scale-invariant asymptotic states of vacuum inhomogeneous cosmologies using renormalization group method. The stability analysis of these states is also given.

General Relativity and Quantum Cosmology · Physics 2009-11-10 J. Ibanez , S. Jhingan

Dynamic equations for quantum fields far from equilibrium are derived by use of functional renormalisation group techniques. The obtained equations are non-perturbative and lead substantially beyond mean-field and quantum Boltzmann type…

Other Condensed Matter · Physics 2008-11-27 Thomas Gasenzer , Jan M. Pawlowski

For a family of second-order parabolic systems with rapidly oscillating and time-dependent periodic coefficients, we investigate the asymptotic behavior of fundamental solutions and establish sharp estimates for the remainders.

Analysis of PDEs · Mathematics 2017-11-30 Jun Geng , Zhongwei Shen

A recently developed variational resummation technique, incorporating renormalization group properties consistently, has been shown to solve the scale dependence problem that plagues the evaluation of thermodynamical quantities, e.g.,…

High Energy Physics - Phenomenology · Physics 2017-12-20 Gabriel N. Ferrari , Jean-Loic Kneur , Marcus B. Pinto , Rudnei O. Ramos

We investigate the renormalization of ``nonlocal" interactions which arise as an infinite sum of higher derivative interactions in an effective field theory. Using dimensional regularization with minimal subtraction in a general scalar…

High Energy Physics - Phenomenology · Physics 2009-10-22 Vineer Bhansali

We present a novel technique for the calculation of dynamical correlation functions of quantum impurity systems in equilibrium with Wilson's numerical renormalization group. Our formulation is based on a complete basis set of the Wilson…

Strongly Correlated Electrons · Physics 2009-11-11 Robert Peters , Thomas Pruschke , Frithjof B. Anders

In this work, an efficient approximation scheme has been proposed for getting accurate approximate solution of nonlinear partial differential equations with constant or variable coefficients satisfying initial conditions in a series of…

Analysis of PDEs · Mathematics 2020-09-04 Prakash Kumar Das , M. M. Panja

The aim of this paper is to establish a nonlinear variational approach to the reconstruction of moving density images from indirect dynamic measurements. Our approach is to model the dynamics as a hyperelastic deformation of an initial…

Numerical Analysis · Mathematics 2015-12-01 Martin Burger , Jan Modersitzki , Sebastian Suhr

We provide a detailed Dynamic Renormalization Group study for a class of stochastic equations that describe non-conserved interface growth mediated by non-local interactions. We consider explicitly both the morphologically stable case, and…

Statistical Mechanics · Physics 2014-01-28 Matteo Nicoli , Rodolfo Cuerno , Mario Castro

A class of (1+2)-dimensional diffusion-convection equations (nonlinear Kolmogorov equations) with time-dependent coefficients is studied with Lie symmetry point of view. The complete group classification is achieved using a gauging of…

Mathematical Physics · Physics 2017-10-02 Olena Vaneeva , Yuri Karadzhov , Christodoulos Sophocleous

In this paper we study the asymptotic behaviour of a nonlocal nonlinear parabolic equation governed by a parameter. After giving the existence of unique branch of solutions composed by stable solutions in stationary case, we gives for the…

Analysis of PDEs · Mathematics 2010-03-23 Armel Andami Ovono

This thesis is devoted to studying aspects of real-time nonequilibrium dynamics in quantum field theory by implementing an initial value formulation of quantum field theory. The main focus is on the linear relaxation of mean fields and…

High Energy Physics - Phenomenology · Physics 2007-05-23 Shang-Yung Wang

We use the local orthogonal decomposition technique to derive a generalized finite element method for linear and semilinear parabolic equations with spatial multiscale diffusion coefficient. We consider nonsmooth initial data and a backward…

Numerical Analysis · Mathematics 2015-05-01 Axel Målqvist , Anna Persson

Diffusion models represent a class of generative models that produce data by denoising a sample corrupted by white noise. Despite the success of diffusion models in computer vision, audio synthesis, and point cloud generation, so far they…

Statistical Mechanics · Physics 2025-01-17 Kanta Masuki , Yuto Ashida